Resolving lexical ambiguity computationally with spreading activation and Polaroid Words. Hirst, G. Small, S., Cottrell, G., & Tanenhaus, M., editors. Lexical ambiguity resolution, pages 73–107. Los Altos, CA: Morgan Kaufmann, 1988. 2003 epilogue to this paper: PDFabstract bibtex Any computer system for understanding natural language input (even in relatively weak senses of the word understanding) needs to be able to resolve lexical ambiguities. In this paper, I describe the lexical ambiguity resolution component of one such system.
The basic strategy used for disambiguation is ``do it the way people do.'' While cognitive modeling is not the primary goal of this work, it is often a good strategy in artificial intelligence to consider cognitive modeling anyway; finding out how people do something and trying to copy them is a good way to get a program to do the same thing. In developing the system below, I was strongly influenced by psycholinguistic research on lexical access and negative priming—in particular by the results of Swinney; Seidenberg, Tanenhaus, Leiman, and Bienkowski; and Reder. I will discuss the degree to which the system is a model of ambiguity resolution in people.
@InBook{ hirst30,
author = {Graeme Hirst},
chapter = {Resolving lexical ambiguity computationally with spreading
activation and Polaroid Words},
title = {Lexical ambiguity resolution},
editor = {Steven Small and Garrison Cottrell and Michael Tanenhaus},
publisher = {Los Altos, CA: Morgan Kaufmann},
year = {1988},
pages = {73--107},
note = {2003 epilogue to this paper: <a
href=http://ftp.cs.toronto.edu/pub/gh/Hirst-88-Epilogue-2003.pdf>PDF</a>}
,
abstract = {<p> Any computer system for understanding natural language
input (even in relatively weak senses of the word
<i>understanding</i>) needs to be able to resolve lexical
ambiguities. In this paper, I describe the lexical
ambiguity resolution component of one such system. </p><p>
The basic strategy used for disambiguation is ``do it the
way people do.'' While cognitive modeling is not the
primary goal of this work, it is often a good strategy in
artificial intelligence to consider cognitive modeling
anyway; finding out how people do something and trying to
copy them is a good way to get a program to do the same
thing. In developing the system below, I was strongly
influenced by psycholinguistic research on lexical access
and negative priming---in particular by the results of
Swinney; Seidenberg, Tanenhaus, Leiman, and Bienkowski; and
Reder. I will discuss the degree to which the system is a
model of ambiguity resolution in people.</p>},
download = {http://ftp.cs.toronto.edu/pub/gh/Hirst-88.pdf}
}
Downloads: 0
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